Feasibility and intra-and interobserver reproducibility of quantitative susceptibility mapping with radiomic features for intracranial dissecting intramural hematomas and atherosclerotic calcifications
Abstract:Quantitative susceptibility mapping (QSM) for 61 patients with dissecting intramural hematomas (n = 36) or atherosclerotic calcifications (n = 25) in intracranial vertebral arteries were collected to assess intra- and interobserver reproducibility in a 3.0-T MR system between January 2015 and December 2017. Two independent observers each segmented regions of interest for lesions twice. The reproducibility was evaluated using intra-class correlation coefficients (ICC) and within-subject coefficients of variatio… Show more
“…First-order features are confounded by large volumes due to the higher number of voxels within the VOI 59 ; thus, as NAWM was the largest VOI in our analysis, we expected a higher degree of variability and this was experimentally confirmed. A recent study assessing the reproducibility of QSM-derived radiomic features in dissecting intramural hematomas and atherosclerotic calcifications of intracranial vertebral arteries also observed volume-dependence of some features with the small volume of the VOIs jeopardising robustness 54 .…”
Section: Discussionmentioning
confidence: 97%
“…The Intraclass Correlation Coefficient (ICC) 53 was measured to evaluate robustness, with 1 indicating perfect repeatability and 0 complete lack of resemblance. Following previous practice 54 , features above a threshold level of ICC > 0.85 were considered to have good reliability. Initial evaluation was performed both overall and by hemisphere (left vs right); the two-sample t-test was used to assess differences between the two sides, with significant p-values < 0.05 considered significant.…”
Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications.
“…First-order features are confounded by large volumes due to the higher number of voxels within the VOI 59 ; thus, as NAWM was the largest VOI in our analysis, we expected a higher degree of variability and this was experimentally confirmed. A recent study assessing the reproducibility of QSM-derived radiomic features in dissecting intramural hematomas and atherosclerotic calcifications of intracranial vertebral arteries also observed volume-dependence of some features with the small volume of the VOIs jeopardising robustness 54 .…”
Section: Discussionmentioning
confidence: 97%
“…The Intraclass Correlation Coefficient (ICC) 53 was measured to evaluate robustness, with 1 indicating perfect repeatability and 0 complete lack of resemblance. Following previous practice 54 , features above a threshold level of ICC > 0.85 were considered to have good reliability. Initial evaluation was performed both overall and by hemisphere (left vs right); the two-sample t-test was used to assess differences between the two sides, with significant p-values < 0.05 considered significant.…”
Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications.
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